How is big data transforming healthcare?

The healthcare industry has always relied on information from patients and medical professionals. In the past, this was analysed and mathematical equations were used to help predict outcomes. 

Scientific and technological advances in the last two decades have exponentially increased the volume and quality of data the healthcare industry can access. It has revolutionised the type of information that can be gathered and how it can be analysed to provide insight on a scale and with levels of accuracy never seen before. 

One of the challenges hospitals have always faced is staffing. Balancing personnel and patient needs is critical. Successfully doing so facilitates the best possible patient outcomes with employee need for rest and recuperation time. Predictive analytics solutions can offer models for early diagnosis, helping to prevent diseases or delay their onset. 

Hospitals in Paris trialled using  big data to predict patient admission rates some years ago. Ten years of admission records, weather, public holidays and flu patterns was analysed by specialist software to develop daily and even hourly predictions of the numbers of patients likely to present for treatment. 

During this unprecedented time, it is also essential to predict as accurately as possible the number of patients that are likely to present for treatment for other serious illnesses so hospitals can manage staffing levels in every area. 

Not all data used in the transformation of healthcare is personal. It is possible to use freely available data on demographics, public health and population growth to future proof an area's healthcare needs. Algorithms can analyse a complex combination of data to identify the need and type of healthcare services an area may require.  

The growth in use of smart and wearable devices, advances in DNA analysis and an increase in online communication means there has never before been as much personalised health related data available.  Now, a variety of apps transform smartphones and wearables into personal health devices, with millions of people harnessing mobile technology to pursue healthier lifestyles. In the near future you might also share this data with your doctor, who will integrate it into their diagnostic toolkit during your visits for health issues.

Although the full potential of this has yet to be realised, medical centres, businesses and insurance companies are beginning to test its potential. For example, 23andMe profiles customers' DNA for potential health risks. The reports provide a personalised indication of the genetic diseases that run in a family and allow customers to take preventative action or prepare accordingly. A pharmaceutical company has created an app that allows diabetes patients to track their blood sugar and meals. It uses this live data to make personalised recommendations for diet and exercise for better diabetes management. 

Big data is assisting the healthcare industry by improving how patients engage with medical professionals. Where before doctors relied on patient recall and tests conducted at a specific point in time, patients can now use apps and smart devices to track their day to day wellbeing. This data can, with permission, be accessed by medical professionals to monitor patients. In time this could reduce the need for routine check-ups. 

Big data provides patients, healthcare professionals and related business with great power and with great power comes great responsibility. Getting the most out of big data brings with it some challenges:

Big data may be a game changer when it comes to global healthcare however its potential hinges on the quality of the big data the medical profession can access. If the data provided is inaccurate or outdated the conclusions drawn through analysis or machine learning are not going to be reliable.  

Health information is some of the most personal and private data individuals have on record. It is imperative health data is stored securely, used with permission and in line with authorised purposes. There is legislation covering the storage and use of personal data in most countries and these must be strictly adhered to when it comes to analysing patient records for healthcare purposes. 

There is also the threat of  cyber criminals targeting health-related data, with episodes like the stolen records relating to 80 million patients from Anthem, the second largest US health insurer.

To enable accurate data modelling there is a need for proper structured data. Without accurate structured data, it can be difficult to analyse and visualise the output for specific information.    

Although big data is leading to systemic changes in the healthcare industry, there are still challenges to be overcome before we can fully benefit from all this new strand of healthcare has to offer. 
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